Paola Malerba, PhD, is an applied mathematician who has dedicated her studies to neuroscientific research. Her work focuses on understanding how neural networks produce brain rhythms and what role they play in brain function. Her interdisciplinary expertise starts from dynamical systems and includes collaborations with behavioral neuroscientists, psychologists, electrophysiologists and clinicians. She has publications in data analysis and modeling the electrophysiology of single cells, modelling of biophysical network oscillations with emphasis on the role of heterogeneity and noise, and study of spatio-temporal patterns in human EEG.
At Nationwide Children's Hospital, she is studying sleep rhythms in the human brain. Sleep helps us embed our memories in our understanding of the world. Specific brain oscillations found during sleep are crucial for this process, and their presence and coordination across brain regions promotes memory performance. Furthermore, non-invasive sleep interventions including targeted memory reactivation (with sound) and transcranial electrical stimulation (aiming at specific brain waves) are capable to enhance sleep oscillations and memory and motor performance. However, it is unknown how these rhythms emerge, organize or how they mediate memory consolidation. In recent work (Sleep 2018), Paola and collaborators have introduced a data-driven EEG analysis method to classify sleep slow oscillations (SOs, a hallmark of deep sleep) depending on their topography on the electrode manifold. This work is opening a new line of research: introducing a new theory of sleep-dependent consolidation in the presence of brain injury, disease or degeneration. Studying how sleep oscillations changes in these conditions can provide insights on how sleep rhythms influence memory consolidation, and at the same time open avenues for interventions aimed at ameliorating the consequences of brain injuries/disease on cognition and motor skills.